Updated in July, 2025
About
Any statistical and computational methods operate under the constraints imposed by the data generating process. To put it another way, no method can extract information from data beyond what is given by nature. Based on this insight, I study how evolutionary processes shape statistical inference.
I’m currently working on the following topics:
- Graphical algorithms in tree sequences for scalable statistical genetics
- Phylogenetic constraints of molecular language models
- Evolutionary basis of whole-genome regression
I try to convince people that all priors of Bayesian models applied to genetic data implicitly (or explicitly) represent the underlying evolutionary process.
Contact: hblee@umich.edu
Education
University of Michigan, Ann Arbor
- Doctor of Philosophy, Department of Statistics (2024.9 -)
Seoul National University
- Doctor of Medicine, Department of Medicine (2016.3 - 2023.8)
- Bachelor of Mathematics, Department of Mathematical Sciences (2017.3 - 2023.8)
Professional service
Peer review
International Journal of Epidemiology, Nature Communications, Genetics (GSA), HGG Advances
Publications
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*: Equal contribution
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Preprints
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Hanbin Lee,
Nathaniel S. Pope, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
Modelling complex traits with ancestral recombination graphs.
bioRxiv,
2025
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Hanbin Lee,
Nathaniel S. Pope, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
Modelling complex traits with ancestral recombination graphs.
bioRxiv,
2025
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Journals
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Brieuc Lehmann,
Hanbin Lee, Luke Anderson-Trocme, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
On ARGs, pedigrees, and genetic relatedness matrices.
Genetics,
2025
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Hanbin Lee,
Rosalind F. Craddock, Gregor Gorjanc, and Hannes Becher
randPedPCA: Rapid approximation of principal components from large pedigrees.
Genetics Selection Evolution,
2025
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Hanbin Lee*, Moo Hyuk Lee*,
Kangcheng Hou, Bogdan Pasaniuc, and Buhm Han
Admixed and single-continental genome segments of the same ancestry have distinct linkage disequilibrium patterns.
Genome Biology,
2025
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Hanbin Lee,
and Buhm Han
Pseudobulk with proper offsets has the same statistical properties as generalized linear mixed models in single-cell case-control studies.
Bioinformatics,
2024
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Hanbin Lee,
and Buhm Han
FastRNA: an efficient exact solution for PCA of single-cell RNA sequencing data based on a batch-accounting count model.
American Journal of Human Genetics,
2022
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Hanbin Lee,
and Buhm Han
A theory-based practical solution to correct for sex-differential participation bias.
Genome Biology,
2022
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Chanwoo Kim*, Hanbin Lee*,
Juhee Jeong, Keehoon Jung and Buhm Han
MarcoPolo: a clustering-free approach to the exploration of differentially expressed genes along with group information in single-cell RNA-seq data.
Nucleic Acids Research,
2022
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Brieuc Lehmann,
Hanbin Lee, Luke Anderson-Trocme, Jerome Kelleher, Gregor Gorjanc, and Peter L. Ralph
On ARGs, pedigrees, and genetic relatedness matrices.
Genetics,
2025